bobai_burned
Read-only
Total $BOBAI permanently burned (sent to the dead/zero address by the autonomous 24/7 buyback-and-burn bot).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
bobai
TDQS
A4.2/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already carry readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: the burn is permanent, executed by an autonomous 24/7 bot, and targets the dead/zero address. This clarifies the return value's significance and permanence beyond what annotations alone provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One well-structured sentence delivers all essential meaning with zero waste. The phrasing is tight and directly informative, hitting the key facts (permanent burn, target address, autonomous bot) without filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a parameterless tool with no output schema, the description is sufficiently complete: it tells the agent exactly what this metric represents and why it matters. Minor gap: it does not specify units (e.g., $BOBAI count vs USD value) or whether the total is updated in real time, but the phrase 'Total $BOBAI' strongly implies token count.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage (empty schema), there is nothing to document. The description explains what the value represents, effectively preempting any confusion about the meaning of the returned figure. This is a baseline-4 case for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description is specific and transparent: states exact resource (total $BOBAI permanently burned) and mechanism (sent to dead/zero address by autonomous 24/7 buyback-and-burn bot). This clearly distinguishes it from sibling tools like bobai_circulating_supply or bobai_price, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is a read-only metric for checking cumulative burned amount, but does not explicitly state when to prefer it over sibling tools or mention any caveats (e.g., data freshness, chain, or whether this includes all burn events). It provides context but no explicit exclusion or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
A3.7/5.0
Disambiguation3/5
Several tools operate on overlapping data: bobai_burned, bobai_activity, and bobai_smart_money all report burn-related metrics, while bobai_token_info, bobai_circulating_supply, and bobai_burned overlap on supply numbers. The long descriptions mitigate this, but the purpose boundaries are less crisp than ideal. The BSC pool tools are more easily told apart.
Naming Consistency3/5
Most token tools use a consistent bobai_* snake_case prefix, but the set mixes conventions: bnb_agent_*, bsc_pool_scan, find_agents_on_bnb_chain, and pancakeswap_fee_tiers break the pattern. The names are still readable and mostly noun-oriented. There is no chaotic mixing of camelCase or vague verbs, but the pattern is not uniform.
Tool Count3/5
19 tools sits in the borderline heavy range for a token research server. Many are focused data views, but some could be consolidated, such as bobai_token_info with circulating supply/burned, or the informational guide/links/tokenomics cluster. Each tool has a defensible role, but the overall surface feels padded.
Completeness4/5
Core workflows are well covered: price, liquidity, DEX parameters, purchase guidance, burns, wallet balances, and BNB agent discovery. Missing historical price/volume, holder distributions, or detailed per-agent profiles, but these are minor gaps rather than dead ends. The server gives an agent what it needs to understand and interact with $BOBAI.